1. Field of the Invention
The present invention relates to an image processing apparatus, image processing method and a program, which execute copy processing and transmission processing using, for example, a scanner and, more particularly, to an image processing apparatus, image processing method and a program, which use a super-resolution technique.
2. Description of the Related Art
A technique called “super-resolution”, which enhances a resolution using a plurality of images having a given resolution, is known. With this technique, an image of 600 dpi can be converted into an image of 1200 dpi or the equivalent, and a conventional device can be used to obtain an image having a higher resolution. In the present specification, when an image is converted into pixels, the number of pixels (i.e., a pixel density) per unit length or per unit area of that image is called a resolution of the image. In order to attain the super-resolution technique, since a plurality of images having different phases in sub-pixel units (a unit smaller than one pixel) is necessary, the super-resolution technique is prevalently applied in the field of moving image processing and the like.
However, since the super-resolution processing requires a plurality of images per pixel, the required memory size and calculation volume increase. Hence, a technique which specifies an area of interest from low-resolution input images and increases/decreases the number of images to be synthesized based on the area size, so as to reduce the calculation volume and memory size, has been proposed (for example, see Japanese Patent Laid-Open No. 2006-092450). Also, a technique which separates input images into emphasis areas and non-emphasis areas and sets the number of low-resolution images to be used for non-emphasis areas smaller than that for emphasis areas, so as to reduce the calculation volume and memory size, has been proposed (for example, see Japanese Patent Laid-Open No. 2005-354124).
In the aforementioned related arts, the user designates emphasis areas or emphasis areas are automatically decided from areas where luminance values are not different in a plurality of images, thus deciding the number of input images used in the super-resolution processing.
However, whether or not high-resolution processing is required for an input image of a multi-functional peripheral equipment (MFP) cannot be determined based only on the size of an area of interest and luminance difference. For this reason, low-resolution processing is often applied to an input image that requires high-resolution processing. For example, when a complicated image such as a map or an image of a brochure including many fine characters are input, they undergo low-resolution processing in the related art, and a problem of crushed small characters is posed even though it has been decided that luminance values are not different in a plurality of images.
When OCR processing is executed for an input image that has a low resolution, particularly, characters of small points are recognized as wrong characters or not recognized, resulting in low character recognition precision.